Cause and Effect

Cause and Effect

• Usually the main reason for a correlational study is to prove that a change in X produces a change in Y.• For example a school board may want to know whether calculators help

students learn math

• However, a strong correlation does not prove that one variable causes the other to change.• For example, after WW2, there is a strong positive correlation between the

number of storks and the annual number of human births in Copenhagen.

What Causes what!!!!

Cause and Effect

Types of Causal Relationship

• We are going to look at the different relationships between variables we might see

Cause and Effect Relationship

• A change in X ACTUALLY produces a change in Y• Increasing the height from which you drop and object increases its impact

velocity.• Increasing the speed of a production line increases the number of items

produced.

Common Cause Factor

• An external Variable causes both variables to change in some way• A town finds that revenue from parking fee’s at the public beach each

summer correlates with the sales at local restaurants

• Good weather is the common cause factor that increases both variables.

Reverse Cause and Effect

• The dependent and independent variable are reversed in the process of establishing causality.• A researcher finds a positive linear correlation between the amount of coffee

consumed by a group of medical students and their levels of anxiety.

• Researchers theorize that drinking coffee causes nervousness, but instead finds that nervous people are more likely to drink coffee.

Accidental Relationship

• A correlation exists without any causal relationship• The number of females enrolled in an engineering program and the number

of reality shows on TV both increased for several years.

• The correlation is likely coincidental.

Presumed Relationship

• A correlation does not seem to be accidental even though no cause-and-effect relationship or no common-cause factor is apparent.

• Suppose you found a correlation between peoples level of fitness and the of adventure movies they watched.• It seems logical that a fit person might prefer action movies, but it would be

difficult to find a common cause of prove that one variable effects the other.

What kind of Relationship?

• The rate of a chemical reaction increases with temp.

• Cause and Effect- higher temps cause faster reactions

What kind of Relationship?

• A scatterplot of the number of storks in Oldenburg, Germany plotted against the population of the town shows a strong positive correlation

• Reverse Cause and Effect – it turns out that storks nest on house chimneys. More people means, more nesting sites and so more storks.

What kind of Relationship?

• An increase in the number of students enrolled in Data Managements and increase in the number of BWM’s on the road

• Accidental – The correlation between the number of students enrolled in data management and the number of BWM’s is coincidental

What kind of Relationship?

• Heart attack rates drop as fitness clubs bring more revenue.

• Presumed relationship – A negative correlation seems logical however there is no apparent common cause-factor or cause and effect relationship.

Extraneous Variables

• Deterring the nature of causal relationships can be complicated by the presence of extraneous variables.

• These are just other variables that can change an outcome.

Control Group and Experimental group• To reduce the effect of extraneous variables researchers often

compare an experimental group to a control group• Groups should be as similar as possible• Researchers vary the independent variable for experimental group but leave

control group the same.

Control Group and Experimental group• A researcher wants to test a new drug believed to help smokers

overcome the addictive effects of nicotine. One group is given nicotine patches while the second is given an ordinary patch (placebo).

Assignment

• Pg 199-201 #’s 1-4, 6, 10, 14